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<table width="100%" summary="page for ohio"><tr><td>ohio</td><td style="text-align: right;">R Documentation</td></tr></table>

<h2>Ohio Children Wheeze Status</h2>

<h3>Description</h3>

<p>The <code>ohio</code> data frame has 2148 rows and 4 columns. The dataset is a
subset of the six-city study, a longitudinal study of the health effects
of air pollution. 
</p>


<h3>Usage</h3>

<pre>data(ohio)</pre>


<h3>Format</h3>

<p>This data frame contains the following columns:
</p>

<dl>
<dt>resp</dt><dd><p>an indicator of wheeze status (1=yes, 0=no)</p>
</dd>
<dt>id</dt><dd><p>a numeric vector for subject id</p>
</dd>
<dt>age</dt><dd><p>a numeric vector of age, 0 is 9 years old</p>
</dd>
<dt>smoke</dt><dd><p>an indicator of maternal smoking at the first year of
the study</p>
</dd>
</dl>



<h3>References</h3>

<p>Fitzmaurice, G.M. and Laird, N.M. (1993) A likelihood-based method for
analyzing longitudinal binary responses, <em>Biometrika</em> <b>80</b>: 141&ndash;151.
</p>


<h3>Examples</h3>

<pre>
data(ohio)
fit &lt;- geese(resp ~ age + smoke + age:smoke, id=id, data=ohio,
             family=binomial, corstr="exch", scale.fix=TRUE)
summary(fit)
fit.ar1 &lt;- geese(resp ~ age + smoke + age:smoke, id=id, data=ohio,
                 family=binomial, corstr="ar1", scale.fix=TRUE)
summary(fit.ar1)
</pre>


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